where \(n_t\)  denotes the number of participants assigned to treatment \(t \in \lbrace 0, 1\rbrace \)  of the index trial, \(y_{i,t}\)  represents the observed clinical outcome for subject \(i\)  in arm \(t\) , and \(\hat{w}_{i,t}\)  is the weight assigned to patient \(i\)  under treatment \(t\) . For binary outcomes, \(\hat{\mu }_t\)  would estimate the expected marginal outcome probability under treatment \(t\) . Absolute outcome estimates may be desirable as inputs to health economic models [1]} or in unanchored comparisons made in the absence of a common control group.
